This guide has explained how to implement some classical machine learning classifiers using the CMSIS-DSP. The guide has shown how to train the classifiers in Python, how to dump the parameters, and how to use the dumped parameters in CMSIS-DSP.
If you want to explore these concepts further, Kaggle has some useful applications of those classifiers.
Thank you for reading our guide on implementing classical ML classifiers with CMSIS-DSP. We look forward to seeing what you can create with CMSIS-DSP.
If you have any questions when using CMSIS-DSP, create a GitHub issue.